There exist numerous techniques for synthesizing images such as those of human faces. These techniques find application both in creating still images of faces, and in animating sequences of such images to create moving pictures in which such faces may speak and otherwise move.
Human face animation has traditionally been performed by drawing a large number of individual frames that are displayed in sequence. This process is notoriously labor-intensive and often requires large numbers of artists working together to generate enough frames for a film "clip" of any significant length.
One early technique for synthesizing single images of faces involved horizontally dividing the image of a face into bands for hair, eyes, nose, mouth, and chin, respectively. Paper strips containing exemplary features could then be combined to form a "composite" drawing of a face. Such techniques found application in law enforcement, where composite drawings were created to aid in the identification of criminal suspects.
More modern techniques base animation on photographic images of actual people, or generate three-dimensional computer models that are projected to a screen for display. Human physiognomy has also been mathematically modeled based on the underlying musculature or photographic examples. Some mathematical modeling of faces have used a few parameters to control the expression of a synthesized face.
Automated systems that synthesize new images based on interpolation among example images have applicability in a wide range of industries. One disadvantage of known systems, however, is that the number of examples needed to fully populate an "example space" providing all combinations of the extremes of varying features grows quickly to an unmanageable number as the number of varying features increases. For instance, four example images are needed to fully define an example space of a human face animation if the only parameters that vary are (i) whether the face is smiling or not and (ii) whether the face is open-mouthed or closed-mouthed. However, by adding just two more variable parameters, e.g., whether the face has eyes looking left or looking right, and whether the eyelids are open or squinting, increases the number of required examples to 16. In such known systems, the number of examples required to fully populate an example space is, in general, exponential, so that if n features are allowed to vary, 2.sup.n examples will be required. Accordingly, if it is desired for more than a few features to be variable, the number of examples may exceed the storage and processing capabilities of conventional microcomputers.
Several known techniques for image synthesis are described and referenced in S. Librande, EXAMPLE-BASED CHARACTER DRAWING, Thesis for Degree of Master of Science in Visual Studies, Massachusetts Institute of Technology (1992), the contents of which is incorporated herein by reference.
None of the known implementations and techniques, however, have solved the problem of synthesizing and animating a human face based on user provided specification of parameters, using low-cost and simple computer apparatus. Furthermore, none of the known implementations and techniques have provided a usable system for people who are neither artists nor technically inclined to draw human faces with the aid of a computer.
The limitations of the known implementations and techniques have heretofore circumscribed the uses and applications for image processing of human faces and other objects, and further have slowed the development of image processing applications that might benefit from an implementation not burdened by such limitations.